Evidence map›Paper›PMID 39169820›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Multimodal Intelligent Flooring System for Advanced Smart-Building Monitoring and Interactions.

Yuqi Chen, Jianlong Hong, Yukun Xiao, Huiyun Zhang, Jun Wu, Qiongfeng Shi

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yuqi ChenJoint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, China.
Jianlong HongJoint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, China.
Yukun XiaoJoint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, China.
Huiyun ZhangJoint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, China.
Jun WuJoint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, China.
Qiongfeng ShiJoint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing, 210096, China.ORCID https://orcid.org/0000-0002-5979-1420

Funding

Fundamental Research Funds for the Central Universities 2242024K40015Nanjing Science and Technology Innovation Project for Returned Overseas Talent 4206002302National Key R&D Program of China 2021YFB3600502National Key R&D Program of China 2022YFB3603403National Natural Science Foundation of China 62075040National Natural Science Foundation of China 62301150Southeast University Interdisciplinary Research Program for Young Scholars 2024FGC1007Start-up Research Fund of Southeast University RF1028623164
6 · The paper itself

Abstract

The floor constitutes one of the largest areas within a building with which users interact most frequently in daily activities. Employing floor sensors is vital for smart-building digital twins, wherein triboelectric nanogenerators demonstrate wide application potential due to their good performance and self-powering characteristics. However, their sensing stability, reliability, and multimodality require further enhancement to meet the rapidly evolving demands. Thus, this work introduces a multimodal intelligent flooring system, implementing a 4 × 4 floor array for multimodal information detection (including position, pressure, material, user identity, and activity) and human-machine interactions. The floor unit incorporates a hybrid structure of triboelectric pressure sensors and a top-surface material sensor, facilitating linear and enhanced sensitivity across a wide pressure range (0-800 N), alongside the material recognition capability. The floor array is implemented by an advanced output-ratio method with minimalist output channels, which is insensitive to environmental factors such as humidity and temperature. In addition to multimodal sensing, energy harvesting is co-designed with the pressure sensors for scavenging waste energy to power smart-building sensor nodes. This developed flooring system enables multimodal sensing, energy harvesting, and smart-sport interactions in smart buildings, greatly expanding the floor sensing scenarios and applications.

Indexed as

flooring systemhuman–machine interactionmultimodalsmart buildingtriboelectric nanogenerator

Identifiers

PMID39169820
PMCPMC11516046

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.